Methods and systems for determining a noise-robust acquisition configuration for operating a sensor system

ABSTRACT

Systems and methods of determining a noise-robust acquisition configuration for a sensor or communication system are disclosed. An exemplary method comprises a noise scan with: obtaining a sensor receive signal from the sensor system; determining a digital receive signal from the sensor receive signal by A/D conversion of the sensor receive signal at a predefined noise scan frequency; determining a plurality of decimated digital receive signals by integer decimation of the digital receive signal using two or more decimation rates that differ from each other, wherein each of the two or more decimation rates is associated with a respective candidate acquisition configuration; determining one or more noise measures for multiple of the candidate acquisition configurations using one or more of the plurality of decimated digital receive signals; and using the one or more noise measures, determining the acquisition configuration for operation of the sensor system from the candidate acquisition configurations.

CROSS REFERENCE TO RELATED APPLICATION

This application claims priority to U.S. Provisional Patent Application63/126,137, filed on Dec. 16, 2020 with the United States Patent andTrademark Office. The contents of the aforesaid patent application areincorporated herein for all purposes.

FIELD

The present disclosure relates to methods and systems for determining anoise-robust acquisition configuration, in particular for a sensorsystem.

BACKGROUND

This background section is provided for the purpose of generallydescribing the context of the disclosure. Work of the presently namedinventor(s) as well as aspects of the description that may not otherwisequalify as prior art at the time of filing, are neither expressly norimpliedly admitted as prior art against the present disclosure.

Sensor systems, sometimes also referred as ‘sensing systems’ are knownfor various applications. For example, capacitive touch sensor systemsare being used for user interfaces of electronic devices, such ascomputers, tablets, smart phones, and other electronic devices.

Capacitive touch sensor systems can be realized, for example, bygenerating an alternating electrical field and measuring the potentialdifference (i.e., the voltage) obtained in one cycle at a sensorelectrode within this field. A single electrode or a combination of atransmitting and one or more receiving electrodes may be used. Thisvoltage is a measure for the capacitance between the sensor electrodeand its electrical environment, i.e., it is influenced by objects like ahuman finger or a hand. Alternatively, an electric current flowingbetween an electrode and the sensor circuit (i.e., motion of electricalcharges), can be used to determine the capacitance between the sensorelectrode and its electrical environment.

A problem with conventional systems operating according to theabove-mentioned principle is that electrical noise sources, such asswitched-mode power supplies, fluorescent lamps, or radio communicationin the vicinity of the sensor can affect the electrical field. Thus,accurately and reliably estimating this voltage in a noisy environmentis problematic.

As the instant inventor has determined, robustness to noise is achallenge for any sensor system, including capacitive touch sensingsystems, and also for communication systems. Particularly, the passingof standard International Electrotechnical Commission (IEC) conductednoise tests, e.g. with amplitude modulated noise as in IEC 61000-4-6,bulk current injection (BCI) tests, e.g. according to the ISO 11452-4automotive standard, or robustness to square noise have been problematicin the past.

SUMMARY

Based on the preceding, a need exists to allow a noise-robust operationof a sensor system, such as for example a capacitive touch sensorsystem. The object is solved by the subject matter of the independentclaims. The dependent claims and the following description comprisevarious embodiments of the invention.

In general and in one exemplary aspect, a method of determining anoise-robust acquisition configuration for operation of a sensor systemis provided. The method comprises the following steps in a noise scan:

obtaining a sensor receive signal from the sensor system;

determining a digital receive signal from the sensor receive signal byA/D conversion of the sensor receive signal at a predefined noise scanfrequency;

determining a plurality of decimated digital receive signals by integerdecimation of the digital receive signal using two or more decimationrates that differ from each other, wherein each of the two or moredecimation rates is associated with a respective candidate acquisitionconfiguration;

determining one or more noise measures for multiple of the candidateacquisition configurations using one or more of the plurality ofdecimated digital receive signals; and

using the one or more noise measures, determining the acquisitionconfiguration for operation of the sensor system from the candidateacquisition configurations.

In general and in another exemplary aspect, a sensor circuit is providedto determine an acquisition configuration for operation of a sensorsystem, comprising:

a sensor interface for obtaining a sensor receive signal from the sensorsystem;

an A/D converter to determine digital receive signal from the sensorreceive signal by A/D conversion of the sensor receive signal at apredefined noise scan frequency;

a decimation circuit, configured to determine a plurality of decimateddigital receive signals by integer decimation of the digital receivesignal using two or more decimation rates that differ from each other,wherein each of the two or more decimation rates is associated with arespective candidate acquisition configuration;

a noise evaluation circuit, configured to determine one or more noisemeasures for multiple of the acquisition configurations using one ormore of the plurality of decimated digital receive signals; and

a configuration circuit, configured to determine the acquisitionconfiguration for operation of the sensor system from the candidateacquisition configurations using the one or more noise measures.

In general and in another exemplary aspect, a capacitive touch sensingsystem is provided, comprising:

one or more electrodes, configured for capacitive sensing; and

the sensor circuit of the preceding aspect, wherein the sensor circuitis connected to at least one of the one or more electrodes.

In general and in another exemplary aspect, a method of determining anoise-robust acquisition configuration for operation of a communicationsystem is provided. The method comprises the following steps in a noisescan:

-   -   obtaining a receive signal from the communication system;    -   determining a digital receive signal from the receive signal by        A/D conversion of the receive signal at a predefined noise scan        frequency;    -   determining a plurality of decimated digital receive signals by        integer decimation of the digital receive signal using two or        more decimation rates that differ from each other, wherein each        of the two or more decimation rates is associated with a        respective candidate acquisition configuration;    -   determining one or more noise measures for multiple of the        acquisition configurations using one or more of the plurality of        decimated digital receive signals; and    -   using the one or more noise measures, determining the        acquisition configuration for operation of the communication        system from the candidate acquisition configurations.

In general and in another exemplary aspect, a communication circuit todetermine an acquisition configuration for operation of a communicationsystem is provided. The communication circuit comprises:

-   -   a communication system interface for obtaining a receive signal        from the communication system;    -   an A/D converter to determine digital receive signal from the        receive signal by A/D conversion of the receive signal at a        predefined noise scan frequency;    -   a decimation circuit, configured to determine a plurality of        decimated digital receive signals by integer decimation of the        digital receive signal using two or more decimation rates that        differ from each other, wherein each of the two or more        decimation rates is associated with a respective acquisition        configuration;    -   a noise evaluation circuit, configured to determine one or more        noise measures for multiple of the acquisition configurations        using one or more of the plurality of decimated digital receive        signals; and    -   a configuration circuit, configured to determine the acquisition        configuration for operation of the communication system from the        candidate acquisition configurations using the one or more noise        measures.

The details of one or more embodiments are set forth in the accompanyingdrawings and the description below. Other features will be apparent fromthe description, drawings, and from the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows a first exemplary embodiment of a sensor circuit in aschematic block diagram;

FIG. 2 shows an exemplary embodiment of a capacitive touch sensingsystem in a schematic view;

FIG. 3 illustrates the functionality of the sensor circuit of FIG. 1 inan exemplary flow diagram according to a first embodiment;

FIG. 4 schematically illustrates the functionality of a decimationcircuit of the sensor circuit of FIG. 1;

FIG. 5 schematically illustrates two signal processing chains for anoise scan and an SN-scan;

FIG. 6 illustrates the functionality of the sensor circuit of FIG. 1 inan exemplary flow diagram according to a second embodiment;

FIG. 7 shows exemplary magnitudes of an ideal ADC's transfer function ina schematic diagram;

FIGS. 8A and 8B illustrates the functionality of the sensor circuit ofFIG. 1 in an exemplary flow diagram according to a further embodiment;

FIG. 9 illustrates spectral noise suppression by digital LPF;

FIG. 10 illustrates the functionality of the sensor circuit of FIG. 1 inan exemplary flow diagram according to another embodiment;

FIG. 11 shows a basic exemplary diagram for charge measurement usingcurrent integration and a corresponding timing diagram;

FIG. 12 shows another exemplary diagram for charge measurement using twocurrent integrators together with a corresponding timing diagram;

FIG. 13 schematically shows two slices of an exemplary analog front-end(AFE) of a touchscreen controller;

FIG. 14 shows an exemplary timing diagram for current integration andintegrator resetting with slice-independent control of aperture andreset switches;

FIG. 15 shows an exemplary timing diagram for current integration andintegrator resetting without slice-independent control of aperture andreset switches;

FIG. 16 shows data obtained using the timing configuration of FIG. 15;and

FIG. 17 illustrates spectral noise suppression by digital LPF for twopacket lengths.

DETAILED DESCRIPTION

Specific embodiments of the invention are here described in detail,below. In the following description of embodiments of the invention, thespecific details are described in order to provide a thoroughunderstanding of the invention. However, it will be apparent to one ofordinary skill in the art that the invention may be practiced withoutthese specific details. In other instances, well-known features have notbeen described in detail to avoid unnecessarily complicating the instantdescription.

In the following explanation of the present invention according to theembodiments described, the terms “connected to” or “connected with” areused to indicate a data or signal connection between at least twocomponents, devices, units, processors, circuits, or modules. Such aconnection may be direct between the respective components, devices,units, processors, circuits, or modules; or indirect, i.e., overintermediate components, devices, units, processors, circuits, ormodules. The connection may be permanent or temporary; wireless orconductor based; digital or analog.

In the following description, ordinal numbers (e.g., first, second,third, etc.) may be used as an adjective for an element (i.e., any nounin the application). The use of ordinal numbers is not to imply orcreate any particular ordering of the elements nor to limit any elementto being only a single element unless expressly disclosed, such as bythe use of the terms “before”, “after”, “single”, and other suchterminology. Rather, the use of ordinal numbers is to distinguishbetween like-named elements. For example, a first element is distinctfrom a second element, and the first element may encompass more than oneelement and succeed (or precede) the second element in an ordering ofelements.

In many applications, sensor systems are used. For example, today'selectronic devices, such as smart phones, laptops, tablets, wearables,would be unthinkable without touchscreens, which generally usecapacitive or resistive touch sensor systems. Current developmentsincrease the use of touchscreens in more complex systems, such as cars,airplanes, or industrial equipment.

Robustness to noise is, as mentioned in the preceding, a key challengefor any such sensor system. A particular issue with capacitivetouchscreens is that these, by design, face the user and need to beconfigured so that the used electric field can be influenced, e.g., whenthe user's hand or finger is in proximity. This makes these types oftouchscreens particularly vulnerable to noise from surrounding fields.

Furthermore, and as the inventor has recognized, there are no reliablemeans for determining the expected signal-to-noise ratio (in thefollowing also referred to as ‘SNR’) for a given sensor andconfiguration, which either leads to insufficient output SNR or a wasteof resources, e.g. acquisition time. For a customer of a touch sensingsystem (e.g., a smart phone manufacturer), it is important to yield ahigh touch report rate with reliable and accurate output estimates.Touch report rate hereby refers to the rate at which a touch controllerforwards, for example, (x,y) position estimates to a host controller.

There are several impact factors affecting noise robustness of a sensorsystem, for example one or more of the operating frequency (in case of acapacitive sensor system the operating frequency of a so-called‘stimulus signal’) with its associated sampling frequency for A/Dconversion, the scan duration, and the choice of low-pass filtercoefficients. In the context of the present discussion, the set ofconfigurable parameters of the sensor system that influence these impactfactors is understood as the ‘acquisition configuration’ or ‘dataacquisition configuration’ of the sensor system (in the following alsoreferred to as ‘AC’ for simplicity). In some embodiments, theacquisition configuration comprises at least one or more of thefollowing parameters: a sampling frequency for A/D conversion, anoperating frequency (carrier frequency) of a stimulus signal for(acquisition) operation of the sensor system, scan duration, a number ofsamples to be acquired, ‘packet length’, and low-pass filtercoefficients. Different ACs differ in one or more of these parameters.The parameters may be used to configure the ‘analog front-end’ as wellas the digital processing of the sensor control circuit.

The receive signal of a communication or sensing system typically is amixture of the actual information that needs to be received andevaluated, as well as noise. This information can, for example, be ameasure for the capacitance or distance between a sensor electrode and auser's finger. In the case of additive noise, the receive signal simplyis the sum of information and noise. Because typically both theinformation part and the noise part are unknown, the information partcannot be easily extracted from the receive signal—comparable to oneequation with two unknowns which cannot be solved uniquely. What ispossible however is estimating the information part given the noisyreceive signal while making assumptions about properties of information,noise or both, e.g., ‘the information is varying slowly over time’. Theless noise there is, the more accurate the resulting estimate, i.e., thesmaller the estimate uncertainty. Therefore, one would like to employ anacquisition configuration for which there is only little noise, e.g., anacquisition configuration which exhibits less noise in the resultingestimate as compared to another acquisition configuration.

It is possible to conduct a test measurement with the sensor system andto compute a noise measure from this measurement data, which isrepresentative for the amount of noise. Such test measurements are inthe present context referred to as ‘noise scans’.

Noise scans may be conducted for different candidate ACs, and given therespective noise determined, the AC for which the lowest amount of noisewas yielded can be selected. Measurements where the receive signalcontains both the desired information and noise will be referred to assignal-and-noise scan, or ‘SN-scan’. During an SN-scan, the sensor orcommunication system may need to create and emit a stimulus signal toexcite an alternating electric field and to yield the information partat the receive side. From data acquired during a noise scan, estimatesof the amount of noise to be expected during an SN-scan for pre-definedcandidate ACs can be computed. Herein, such an estimate is referred toas ‘noise estimate’. The ACs for which noise estimates are computed fromnoise scan data acquired during a single noise scan may differ at leastin their operating frequency and sampling frequency, which areconsidered parameters of the analog front-end of the sensor system.

In the present context, a ‘stimulus signal’, or simply ‘stimulus’, isunderstood as an actively controlled movement of electrical chargesbetween a sensor circuit, e.g., a chip, and an electrode, for example todrive the electrode's electrical potential to a given target value ortarget signal. In some embodiments, this target value or target signalis specified before the stimulus is initiated; for example, when thetarget signal is a rectangular pulse train with a given pulse frequency,this pulse frequency is selected before driving the electrode'selectrical potential to this target signal.

In some embodiments, the stimulus may be a periodic signal, e.g., arectangular pulse train. The frequency of this periodic signal, e.g. thepulse frequency, is the operating frequency discussed in the preceding,also referred to as ‘carrier frequency’. In some embodiments, thestimulus signal settles alternately to a higher signal level and a lowersignal level each once during a carrier signal period. On the receiveside, the receive(d) signal may be demodulated and low-passfiltered—both of which may be performed in the digital domain afteranalog-to-digital (A/D) conversion. When the stimulus is a rectangularpulse train, sampling may be conducted at twice the carrier frequency insome embodiments. Demodulation may be conducted by alternatinglymultiplying the A/D converted samples with plus one and minus one insome embodiments.

Based on the preceding, a need addressed by embodiments of the inventionis to select a suitable AC from a set of candidate ACs in order toachieve, e.g., a high touch report rate with reliable and accurateoutput estimates.

Basic exemplary ideas of the invention comprise a) the idea of base- andsub-frequencies, allowing to process the same sequence of noise scanmeasurement data in different ways, more precisely with differentparameters, in order to yield reliable noise (power) estimates formultiple ACs (for example with respect to carrier frequencies and scantimes), and b) a robust noise measure providing an accurate estimate forthe true noise power of SN-scan measurement data after demodulation andlow-pass filtering.

According to a first exemplary aspect, a method of determining anoise-robust acquisition configuration for operation of a sensor systemcomprises the following steps in a noise scan:

-   -   obtaining a sensor receive signal from the sensor system;    -   determining a digital receive signal from the sensor receive        signal by A/D conversion of the sensor receive signal at a        predefined noise scan frequency;    -   determining a plurality of decimated digital receive signals by        integer decimation of the digital receive signal using two or        more decimation rates that differ from each other, wherein the        two or more decimation rates are associated with a respective        candidate acquisition configuration;    -   determining one or more noise measures for multiple of the        candidate acquisition configurations using one or more of the        plurality of decimated digital receive signals; and    -   using the one or more noise measures, determining the        acquisition configuration for operation of the sensor system        from the candidate acquisition configurations.

The sensor system of the present aspect may be of any suitable type,including, without limitation, sensor systems to detect and measureproximity, pressure, position, displacement, force, humidity, fluidlevel, and acceleration. For example, the sensor system may be aninfrared sensor system or an ultrasound sensor system. For example, thesensor system may be a capacitive or resistive touch sensor system, suchas for a touchscreen display. For example, the sensor system may be atouch-less sensor system.

In some embodiments, the method of the present aspect is conducted usinga sensor circuit, for example a sensor circuit comprising a controlunit, such as a microcontroller and/or microprocessor with suitableprogramming. Alternatively or additionally, the sensor circuit maycomprise dedicated circuitry that provides at least a part of thefunctionality of the method of this exemplary aspect.

As discussed in the preceding, the noise scan of the present aspect maybe considered a test measurement to determine, e.g., the effects ofnoise on the respective sensor system. In some embodiments, themeasurement data obtained during the noise scan does not contain anyinformation but only noise, i.e., the sensor receive signal during thenoise scan is acquired without a stimulus signal being applied to thesensor system.

The (sensor) receive signal (i.e., a received, measured or acquiredsignal during a noise scan or SN-scan) may be, for example, an electriccurrent flowing between an electrode and the sensor circuit, i.e.,motion of electrical charges, an electric current integrated over acertain time interval, or an electric potential or voltage of theelectrode relative to a reference potential. The sensor receive signalmay be obtained from the sensor system by any suitable means, forexample a corresponding conductive connection.

This receive signal may be affected by the stimulus when used, possiblymodified by environmental factors like a human finger, and is in mostcircumstances affected by environmental noise sources. In addition tothese environmental, or external, impact factors, there can be analogpre-processing within the sensor circuitry which can add furtherinternal noise to the receive signal, for example 1/f noise orquantization noise of an A/D converter. While robustness to noise frominternal sources typically can be addressed during system design,environmental noise sources are at least to some extent unknown atdesign time. The methods and systems discussed herein address robustnessto external noise. Disregarding internal noise, any change in thereceive signal, i.e., any electric current or change in above electricpotential, is caused by this external noise of interest.

According to the first exemplary aspect, the method comprisesdetermining a digital receive signal from the sensor receive signal byA/D conversion of the sensor receive signal at a predefined noise scanfrequency. A/D conversion may be conducted using any suitable method,for example using a flash A/D converter, an integrating A/D converter, asuccessive approximation A/D converter, a sigma-delta A/D converter, adirect-conversion A/D converter, a ramp-compare A/D converter, aWilkinson A/D converter, a charge balancing A/D converter, a dual-slopeA/D converter, a delta-encoded A/D converter, a pipelined A/D converter,a time-interleaved A/D converter, an intermediate FM stage A/Dconverter, a TS-ADC, or any equivalent, without limitation. The term“A/D converter” herein includes setups of an analog front-end with asuitable A/D converter. A/D conversion is conducted at the predefinednoise scan frequency that may be set depending on the application. Insome embodiments, the noise scan frequency is significantly higher thanan operating frequency of a stimulus signal during operation of thesensor system. In some embodiments, the noise scan frequency may be setto at least three times the operating frequency, such as between 3×-40×of the operating frequency. In some embodiments, the noise scanfrequency is set between 3×-4× of the operating frequency.

In some embodiments, the noise scan frequency, i.e., the sampling rateof the A/D converter during a noise scan, may be significantly higherthan the sampling rate of the A/D converter during an SN-scan.Inversely, the sampling interval of the A/D converter may besignificantly shorter for a noise scan as compared with an SN-scan, andso is the time available for the analog processing of the received inputsignal for an analog-to-digital (A/D) converted sample. Consequently,the timing for analog processing desired for an SN-scan may not beapplicable to a noise scan because there is less time between A/Dconversions. Embodiments are discussed in the following using a specificratio of an aperture time for a noise scan to an aperture time for anSN-scan.

According to the first exemplary aspect, the method comprisesdetermining a plurality of decimated digital receive signals by integerdecimation of the digital receive signal using two or more decimationrates that differ from each other.

In other words, after the conducted A/D conversion, i.e., in the digitaldomain, the then digital receive signal is decimated by integerdecimation to obtain the plurality of decimated digital receive signals.At least two different decimation rates are used, each of which isassociated with a respective candidate acquisition configuration. Insome embodiments, the two or more decimation rates are multiples of 2,such as for example, 2 and 4. In some embodiments more than twodecimation dates are used.

The two or more decimation rates are associated with respectivecandidate acquisition configurations, e.g., in light of the resultingdiffering sampling rates when applying the different decimation rates.

According to the present aspect, one or more noise measures for multipleof the candidate acquisition configurations are determined using one ormore of the plurality of decimated digital receive signals. In turn andusing the one or more noise measures, the acquisition configuration foroperation of the sensor system is determined from the candidateacquisition configurations.

As will be apparent from the preceding, the method according to thefirst aspect allows the use of the same measurement data of the sensorreceive signal to determine multiple decimated digital receive signals.Since two or more decimation rates are used, the plurality of decimateddigital receive signals correspondingly have two or more differentsampling frequencies. Since the sampling frequency and the relatedoperating frequency may be part of the acquisition configuration to betested, i.e., the ‘candidate ACs’, the discussed method thus allows,e.g., to use the same measurement data to test multiple differentcandidate ACs.

In some embodiments, oversampling is conducted during a noise scan.Then, to yield the same aliasing (of noise) as for an SN-scan, thedecimation rate for decimating the noise scan signal may for example bechosen such that the decimated sampling rate equals the SN-scan samplingrate.

As opposed to other known approaches, the teachings herein, at least insome embodiments, not only provide a solution for identifying arelatively best carrier frequency, but a complete solution for noiserobustness. Robustness to, e.g., AM noise and square noise is provideddue to the determination of the one or more noise measures from the samemeasurement data but for different ACs. This method also is inherentlyquick and saves measurement time. In some embodiments, the methodfurther allows finding a trade-off between touch report rate and outputSNR.

As discussed in the preceding, the method of the first exemplary aspectcomprises determining one or more noise measures for multiple of the(two or more) candidate acquisition configurations from one or more ofthe plurality of the decimated digital receive signals. Thedetermination of the noise measures may, for example, be conducted inthe digital domain. In some embodiments, one or more noise measures aredetermined for each of candidate acquisition configurations, whichallows for comparison of different candidate ACs. In some embodiments, anoise measure is calculated for each decimation rate from at least onedecimated digital receive signal that is associated with the respectivedecimation rate. In some embodiments, a noise measure is calculated foreach decimation rate from multiple decimated digital receive signals.This method will be discussed in more detail in the following.

The noise measure may be of any suitable type to obtain a comparablemeasure of noise. For example, the noise measure may be a numericalvalue, typically quantifying a noise level present in at least one ofthe plurality of decimated digital receive signals.

The noise measure in some embodiments may be a power measure as, forexample, obtained by effective noise power estimation (ENPE), but it mayalso be, for example, a square root of a power measure or another linearmeasure, i.e., a quantity computed from input data using linearfunctions only, without limitation. In some embodiments, the noisemeasure is a phase-instantaneous noise measure. There are alsoapproaches where the noise measure is a scoring value where a higherscore indicates a lower noise level for an SN-scan, as for examplediscussed in U.S. Ser. No. 10/151,608 B2, incorporated herein for allpurposes.

In some embodiments, there is a stimulus present during a scan toacquire data for computing noise measures, i.e., during the noise scan.While measurement data acquired during a scan of this kind is morelikely to be influenced by, for example, a human finger in the sensor'svicinity, it can still be used to yield a sufficiently good decisionbase for identifying a suitable AC. This in mind, the term ‘powermeasure’ may in some embodiments be used interchangeable with the term‘noise measure’.

Once the one or more noise measures are determined, according to thefirst exemplary aspect, the acquisition configuration for operation ofthe sensor system is determined from the given candidate acquisitionconfigurations. The present determination is based on the one or morenoise measures. As will be discussed in more detail in the following,and in some embodiments, the determination may be influenced by furtherconsiderations, such as for example a shortest scan time (also referredto as ‘scan duration’).

In some embodiments, the step of determining the acquisitionconfiguration comprises selecting a preferred noise measure from the oneor more noise measures, wherein the acquisition configuration is set tocorrespond to the candidate acquisition configuration associated withthe preferred noise measure.

In some embodiments, the preferred noise measure is selected based on apredefined criterium, such as for example based on a predefinedthreshold of maximum noise.

In some embodiments, the preferred noise measure yields the lowest noiselevel of the one or more noise measures. In other words, in theseembodiments, the preferred noise measure can also be referred to as a‘best’ noise measure, wherein the best noise measure is understood as anoise measure whose quantity indicates the lowest noise level comparedto all other noise measures in a given comparison set of noise measures.For example, when the noise measure is determined by ENPE, then the bestnoise measure would have the lowest value, and according to thedisclosure of U.S. Ser. No. 10/151,608B2, it would have the highestvalue.

In some embodiments, for each of the two or more decimation rates,corresponding groups of decimated digital receive signals (i.e., groupsof two or more decimated digital receive signals) are determined as apart of the determination of the plurality of decimated digital receivesignals. Accordingly, and in view of the two or more decimation rates,at least two groups of decimated digital receive signals are providedaccording to the present embodiments, wherein the group ‘members’ of onegroup share the same decimation rate.

In some embodiments, each decimated digital receive signal of a givengroup differs from all other decimated digital receive signals of thegiven group. The group of decimated digital receive signals may differfrom each other in any suitable way. The group of decimated digitalreceive signals may have the same or a different number of samples.

In some embodiments and in each group, the decimated digital receivesignals may differ from each other at least, but without limitation, byhaving a different starting phase. The present embodiments allow afurther improved determination of noise, as will be apparent from thefollowing discussion. The term ‘starting phase’ with respect to digitalsignals is understood as the delay of a decimated signal's first samplerelative to the digital receive signal's first sample, typically in theunit of samples at the receive signal's sampling rate. Accordingly, adifferent starting phase with respect to two signals refers to that thetwo signals have differing starting samples.

As will be easily apparent, not all possible starting phases need to berepresented in a given group of decimated digital receive signals. Forexample, for each of the at least two decimation rates R(0,j) thedigital receive signal x may be decimated for a subset of startingphases v=v0, v0+dv, v0+2dv, . . . , R(0,j)−1, where j=0, 1, . . . isdenoted the sub-frequency index. In other embodiments, a group ofdecimated digital receive signals represent all possible startingphases. For example, for each of the at least two decimation ratesR(0,j), the signal x may be decimated for all starting phases v=0, 1, .. . , R(0,j)−1. Accordingly, in the exemplary case of a digital receivesignal with 24 samples and a decimation rate of four (i.e., R=4), thegroup would comprise four corresponding decimated digital receivesignals with six samples each, and each signal starting at a differentstarting phase of the total of four possible starting phases. While eachof the decimated digital receive signals of the group only comprisesevery fourth sample, due to the phase shift of one sample, every sampleis still represented in the group resulting in an improved noisemeasure.

In some embodiments, the one or more noise measures are determined by aneffective noise power estimation (ENPE), which comprises a determinationof a (e.g., normalized) sum of phase-instantaneous noise measures overeach of the decimated digital receive signals of one of the groups ofdecimated digital receive signals. In some embodiments, the effectivenoise power estimation is conducted for all groups, i.e., for alldecimation rates. The determination of the sum of phase-instantaneousnoise measures can be conducted by any suitable method. In someembodiments, the phase-instantaneous noise measure is a sum of (all)samples of a decimated digital receive signal weighted with coefficientsfrom a coefficient vector. For example, the coefficient vector may be avector containing the coefficients of a low-pass filter. For example,the coefficients of a boxcar window (all ones) or a Hann (or hanning)window of desired length. Normalization of such a sum term can, forexample, be done by dividing this sum term by the sum of allcoefficients in the coefficient vector. This normalization does not needto be done directly on the weighted sum term, but can also be done atlater processing stage, e.g. after summing of phase-instantaneous noisemeasures, which can reduce computational complexity.

For example, to compute the ENPE for a given decimation rate, for eachdecimated digital receive signal of a given group, the dot product withthe assigned coefficient vector is computed. In some embodiments, thesedot products are normalized by dividing by the sum of all coefficients.Then the average of the squared normalized dot products may be computedto yield the ENPE.

In some embodiments, the step of determining the acquisitionconfiguration from the set of candidate acquisition configurationscomprises selecting the candidate acquisition configuration that has theshortest scan time while the noise measure meets a (predefined) noisethreshold. The present embodiments provide a particularly high touchreport rate as the shortest possible scan time is employed.

It is noted that in the context of comparing noise measures with a noisethreshold, it is understood that this also encompasses the alternativeof comparing expected output signal-to-noise ratio (SNR) with a(predefined) SNR threshold. The SNR can be computed from an a prioridetermined signal power and the noise measure determination, discussedin the preceding.

In some embodiments, the step of determining the acquisitionconfiguration from the set of candidate acquisition configurationsfurther comprises comparing the one or more noise measures with a noisethreshold and in case the noise threshold is not met by any of the oneor more noise measures, increasing the scan time of at least one of thecandidate acquisition configurations to obtain at least one updatedcandidate acquisition configuration, determining one or more updatednoise measures for the at least one updated candidate acquisitionconfiguration, and comparing the one or more updated noise measures withthe noise threshold.

The present embodiments allow to gradually evaluate candidateacquisition configurations with increased scan time in case none of theoriginal candidate acquisition configurations meets the desired noisethreshold, which may, e.g., be set in accordance with the respectiveapplication. Correspondingly and in some embodiments, the discussedsteps may be repeated until an acquisition configuration is found thatmeets the noise threshold. In case that, in a given iteration, multiplecandidate acquisition configurations are found that meet the threshold,in some embodiments the candidate acquisition configuration is selectedas acquisition configuration for system operation that has the lowestnoise level for the scan time of the given iteration. In someembodiments, the scan time of multiple or all candidate acquisitionconfigurations is increased in a given iteration of the preceding steps.This provides multiple updated candidate acquisition configurations thatmay have the same operating and sampling frequency, but differentcoefficient vectors.

In some embodiments, the scan time is increased by a substantiallyinteger multiple of a scan time of the original/preceding candidateacquisition configuration. These embodiments are particularly beneficialfor reducing noise. In some embodiments, a ‘substantially integermultiple’ comprises percentage deviations from the integer multiple ofapprox.

${{\pm \frac{100}{T}}\%},$

where T is the original scan time.

To increase the scan time, in some embodiments a new noise scan may beconducted with a correspondingly increased scan time to obtain the atleast one updated candidate acquisition configuration.

In other embodiments, it is possible during the step of obtaining thesensor receive signal from the sensor system to obtain a sensor receivesignal with a maximum scan time and consider only a portion of itinitially. For example and in some embodiments, after the A/D conversionis conducted, only a portion of the sensor receive signal is processedfurther and forms the basis for the discussed decimation, namely with aminimum scan time, while the original sensor receive signal is stored.In these embodiments, it is possible to ‘increase’ the scan time bysubsequently using a longer portion of the stored copy of the originalsensor receive signal, i.e., with increased scan time. In someembodiments, the maximum scan time may be four times the minimum scantime.

In some embodiments, a predefined minimum output report rate for thesensor system may be given, or, inversely, a maximum duration for a scancycle (i.e., the successive operation of one or more noise scans and anSN-scan) during which respective measurement data is acquired. This timeavailable for a scan cycle is distributed over all individualmeasurements to be done during the scan cycle, including auxiliarymeasurements like a noise scan and at least one SN-scan. For example,for one individual measurement of an SN-scan we may thus yield a maximumscan time T. Given an AC with sampling frequency f_(s), e.g.f_(s)=2·f_(c) being twice the operating frequency or carrier frequencyf_(c), it is possible to fit up to

$\lfloor \frac{T}{1/f_{S}} \rfloor\mspace{14mu}{ADC}$

samples into time T. Hence, to fully exploit this available scan time Tit is possible in some embodiments to set the number of samples to beacquired and processed, denoted herein the ‘packet length’ L, for thegiven AC to

$L = {\lfloor \frac{T}{1/f_{s}} \rfloor.}$

In some embodiments and in case a finite input response (FIR) low-passfilter is employed to process the acquired data, the filter length mayalso be set to L in order to make use of all of the acquired data, andbecause a single output value for the data acquired during scan time Tmay be desired, while requiring the low-pass filter output to havesettled. The vector of low-pass filter coefficients may be chosen, forexample, to control the filter's spectral suppression in someembodiments. For example, the vector's first elements can be positivevalues smaller than the middle elements of the vector. For example, sucha vector can be [0.05, 0.1, 0.2, 0.3, 0.2, 0.1, 0.05]. In someembodiments, the vector symmetric. For example, it is possible to choosea Hanning window of length L as the vector of low-pass filtercoefficients. The n-th element of the Hanning window, as defined byMathworks, is

${w_{n} = {\sin( \frac{\pi( {n + 1} )}{L + 1} )}},{0 \leq n \leq ( {L - 1} )}$

In some embodiments, following the noise scan, the method comprisesoperating the sensor system during an SN-scan using the acquisitionconfiguration determined during the noise scan. During the SN-scan, thesensor system may be operated to emit a stimulus signal to excite analternating electric field, which then can be evaluated for therespective sensing application, such as a touch detection.

In some embodiments, the sensor system is operated during the SN-scanusing the acquisition configuration of the latest noise scan in viewthat the acquisition configuration of the latest scan represents themost up-to-date configuration for a current noise scenario. In someembodiments, following the SN-scan, a further noise scan is conducted.The resulting cycled operation may be repeated until the sensingoperation of the sensor system stops in some embodiments, such as whenthe sensor system is powered down.

In some embodiments, the method comprises subsequently conductingmultiple noise scans between two SN-scans, wherein the multiple noisescans use predefined noise scan frequencies, wherein the predefinednoise scan frequencies of at least some (or, e.g., all) of the multiplenoise scans differ from each other. The present embodiments allow tofurther improve the determination of a noise-robust acquisitionconfiguration, in particular when candidate acquisition configurationsare to be evaluated that do not share a common multiple.

For example, it is possible to determine an overall acquisitionconfiguration for operation of the sensor system from acquisitionconfigurations obtained during the subsequently conducted multiple noisescans. In other words, a ‘preferred’ or ‘best’ overall acquisitionconfiguration may be determined from the multiple acquisitionconfigurations obtained in each run of a noise scan. In someembodiments, the overall acquisition configuration may be determinedfrom the group of acquisition configurations, determined during themultiple noise scans, by comparing the associated noise measures and/orrespective scan times.

Alternatively, in some embodiments, it is possible to conduct noisescans for, e.g., only two (or a different number of) predefined noisescan frequencies successively during a scan cycle, while keeping the oneyielding the best AC, and cyclically looping over the remainingcandidate noise scan frequencies to select the second one.

In some embodiments, the aperture time of the A/D conversion fordetermining the acquisition configuration (i.e., during the noise scan)is set to be substantially identical to, or an integer fraction of theaperture time of an SN-scan. In other words, an aperture time ispredefined, or selected as desired, for the SN-scan according to therespective application (e.g., in terms of touch report rate) and theaperture time for the A/D conversion during the noise scan is setaccordingly, i.e., identical or an integer fraction of the predefinedaperture time. In the context of the present invention, the term“aperture time” generally is understood as the time duration for whichan analog signal is input to a measurement system, i.e., the time duringwhich the measurement system is exposed to the outside world and thusits internal analog state is changed by the analog input signal. In someembodiments, the aperture time relates to the time the sensor receivesignal is input to the sensor interface of the sensor circuit, discussedin the following. In some embodiments, the aperture time relates to thetime the sensor receive signal is input to the A/D converter of thesensor circuit, discussed in the following.

When the noise scan aperture time is identical to the SN-scan aperturetime, it is possible to ensure to yield a relatively best carrierfrequency decision. When the noise scan aperture time is an integerfraction of the SN-scan aperture time, and the noise is narrow-band, itis still possible to yield a best carrier frequency, though an absoluteeffective noise power estimate cannot be provided.

As the instant inventor has ascertained, for certain ratios betweenSN-scan and noise scan aperture times, it is possible to ensure to yielda relatively best carrier frequency decision. This is the case when thenoise scan aperture time is either a) identical to the SN-scan aperturetime, or b) when the noise scan aperture time is an integer fraction ofthe SN-scan aperture time or correspondingly, when the SN-scan aperturetime is an integer multiple of the noise scan aperture time.

In some embodiments, (for a given base frequency f^((i)) with basefrequency index i) the duration L_(ρ) ^((i,j))·R^((i,j))/f^((i)) isapproximately the same for all index pairs (i,j).

In some embodiments, the method steps are conducted at least in part bya sensor circuit for a sensor system. In some embodiments, a (e.g.,non-transitory) computer-readable medium is provided with contents thatare configured to cause the sensor circuit to conduct the method stepsas described herein.

According to another aspect, a sensor circuit to determine anacquisition configuration for operation of a sensor system is provided.The sensor circuit comprises, but is not limited to:

-   -   a sensor interface or input for obtaining a sensor receive        signal from the sensor system;    -   an A/D converter to determine a digital receive signal from the        sensor receive signal by A/D conversion of the sensor receive        signal at a predefined noise scan frequency;    -   a decimation circuit, configured to determine a plurality of        decimated digital receive signals by integer decimation of the        digital receive signal using two or more decimation rates that        differ from each other, wherein each of the two or more        decimation rates is associated with a respective candidate        acquisition configuration;    -   a noise evaluation circuit, configured to determine one or more        noise measures for multiple of the candidate acquisition        configurations using one or more of the plurality of decimated        digital receive signals; and    -   a configuration circuit, configured to determine the acquisition        configuration for operation of the sensor system from the        candidate acquisition configurations using the one or more noise        measures.

In some embodiments, the sensor circuit according to the present aspectis configured according to one or more of the embodiments, discussed inthe preceding with respect to the preceding aspect(s). With respect tothe terms used and their definitions, reference is made to the precedingaspect(s).

According to another aspect, a capacitive touch sensing system(capacitive sensor) is provided. The capacitive touch sensing system ofthis aspect comprises:

-   -   one or more electrodes, configured for capacitive sensing; and    -   a sensor circuit, connected to at least one of the electrodes;        wherein the sensor circuit comprises:    -   a sensor interface or input for obtaining a sensor receive        signal from the one or more electrodes;    -   an A/D converter to determine a digital receive signal from the        sensor receive signal by A/D conversion of the sensor receive        signal at a predefined noise scan frequency;    -   a decimation circuit, configured to determine a plurality of        decimated digital receive signals by integer decimation of the        digital receive signal using two or more decimation rates that        differ from each other, wherein each of the two or more        decimation rates is associated with a respective candidate        acquisition configuration;    -   a noise evaluation circuit, configured to determine one or more        noise measures for multiple of the candidate acquisition        configurations using one or more of the plurality of decimated        digital receive signals; and    -   a configuration circuit, configured to determine the acquisition        configuration for operation of the sensor system from the        candidate acquisition configurations using the one or more noise        measures.

In some embodiments, a sensor circuit according to the present aspect isconfigured according to one or more of the embodiments, discussed in thepreceding with respect to the preceding aspect(s). With respect to theterms used and their definitions, reference is made to the precedingaspect(s). The term “capacitive touch sensing system” used herein isunderstood to comprise touch-less sensor systems, e.g., based on adetection of proximity.

Reference will now be made to the drawings in which the various elementsof embodiments will be given numerical designations and in which furtherembodiments will be discussed.

In the exemplary embodiments, the described components of theembodiments each represent individual features that are to be consideredindependent of one another, in the combination as shown or described,and in combinations other than shown or described. In addition, thedescribed embodiments can also be supplemented by features of theinvention other than those described.

FIG. 1 shows a first exemplary embodiment of a sensor circuit 1 in aschematic block diagram. The sensor circuit 1 is adapted to operate asensor system or a communication system (both not shown in FIG. 1). Forexample, a sensor 20 of a capacitive touch sensing system 21, shownschematically in FIG. 2, may be connected to sensor circuit 1. For thesake of the present discussion, reference will be made to capacitivetouch sensing system 21, even though it is emphasized that the inventionis not limited to capacitive touch sensing systems.

The exemplary sensor circuit 1 of the embodiment of FIG. 1 may beembodied by a microcontroller, with hardware/software that provides thefollowing operation and components. For improved clarity, themicrocontroller itself is not shown in the schematic block diagram ofFIG. 1.

The sensor circuit 1 comprises a sensor interface 2, which isconnectable to the sensor 20 of capacitive touch sensing system 21,using sensor connections 3. Capacitive touch sensing is known, forexample, for use in capacitive touch screen panels of electronicdevices, such as computers, tablets, smart phones, wearables, and smarthome equipment, and electronic components for vehicles, trains, ships,air-/spacecraft, and industrial or scientific equipment, withoutlimitation. In one example, the capacitive touch sensing system 21 is a‘touch-less’ sensor system.

The sensor interface 2 and sensor connections 3 allow the sensor circuit1 to operate/drive the sensor 20 of capacitive touch sensing system 21during acquisition operation, which is referred to herein as‘signal-and-noise scan’, or SN-scan. During an SN-scan, the sensorcircuit 1 or more precisely a drive circuit 4 of sensor circuit 1creates and transmits a stimulus signal to excite an alternatingelectric field near the sensor 20 of capacitive touch sensing system 21,which then yields the information part at the receive side, namely withrespect to the capacitive touch sensing, whether one or more fingers ofa user or a different object are detected close to the surface of sensor20. Both, the transmission of the stimulus signal and the reception of areturning sensor receive signal is handled by sensor interface 2. Forthe purposes of the present discussion and by way of example, thestimulus signal is a periodic signal, namely a rectangular pulse train.The frequency of this periodic signal, i.e., the pulse frequency, isreferred to as the operating frequency or carrier frequency of theSN-scan.

In addition to the acquisition operation, sensor circuit 1 conductsnoise scans in a corresponding noise scan mode. During a noise scan,preferably no stimulus signal is applied to the sensor by the sensorcircuit 1.

The noise scans, as discussed in the preceding, serve as testmeasurements and allow computation of noise measures from measurementdata obtained during the noise scans, which are representative of theamount of noise to be expected during an SN-scan. Robustness to noise isa key challenge for any communication system or sensor system, includingcapacitive touch sensing system 21. Particularly, the passing ofstandard IEC conducted noise tests, e.g., with amplitude modulated noiseas in IEC 61000-4-6, bulk current injection (BCI) tests, e.g. accordingto the ISO 11452-4 automotive standard, or robustness to square noise isaddressed. Further, for various applications of the capacitive touchsensing system 21, it is important to yield a high touch report ratewith reliable and accurate output estimates.

A goal of conducting the noise scans is to determine an acquisitionconfiguration for operation of the capacitive touch sensing system 21during an SN-scan. The acquisition configuration comprises one or moreparameters for the operation of the capacitive touch sensing system 21during an SN-scan and may comprise one or more of a sampling frequencyfor A/D conversion, an operating frequency (carrier frequency) of thestimulus signal for (acquisition) operation of the sensor system, scanduration, a number of samples to be acquired, and low-pass filtercoefficients.

It is noted that for the present discussion, the sampling frequency forA/D conversion during an SN-scan is considered to be related to theoperating frequency/carrier frequency of the stimulus signal. One reasonfor this relationship is that the sensor receive signal in the presentembodiment is a quasi-static signal, i.e., a signal which does not, oronly hardly, changes over time during given time intervals, in view ofthe stimulus signal in the shape of a rectangular pulse train. On thereceive or sensing side and as discussed in the following, when thesignal has experienced low-pass filtering, its edges are rounded andafter each edge it shows a transition duration until it settles to aconstant level. Herein, the received signal is sampled once after eachedge when the signal has settled to a sufficient extent, i.e., there aretwo samples per period of the rectangular pulse train during theSN-scan, thus corresponding to the sampling frequency being twice thecarrier frequency.

Sensor circuit 1 further comprises A/D converter 5, digital signalprocessing circuit 15, noise evaluation circuit 8, configuration circuit9, memory 10, touch detector 11, and output 12. The digital signalprocessing circuit 15 comprises in particular a decimation circuit (notshown in FIG. 1) that is configured to determine a plurality ofdecimated digital receive signals, as discussed in more detail in thefollowing. It is noted that FIG. 1 does not show all control connectionsbetween the aforementioned components, e.g., for controlling thesampling rate of A/D converter 5 or access of memory 10 by signalprocessing circuit 15.

During a noise scan, the signal processing chain of A/D converter 5,digital signal processing circuit 15, noise evaluation circuit 8, andconfiguration circuit 9 is active.

During the SN-scan, the noise evaluation circuit 8, and theconfiguration circuit 9 are disabled, or inactive. In this case, thesensor receive signal, after A/D conversion and signal processing isprovided to touch detector 11 for determination of a user touch on thesensor 20. The result is provided to a connected external component viaoutput 12.

The functionality of sensor circuit 1 and its components will in thefollowing be explained referring to FIG. 1 and the flow diagram FIG. 3.

For simplicity of illustration, it is assumed that exemplary capacitivetouch or touch-less sensing system 21 has a multitude of acquisitionconfigurations, whose analog front-end parameters are equal but for theoperating frequencies and the respective sampling frequencies, thelatter of which, as discussed in the preceding, are twice the carrierfrequencies in this exemplary embodiment. The different samplingfrequencies have a common multiple, which is the predefined noise scanfrequency. Other, digital signal processing parameters, like the numberof samples to be filtered and the choice of low-pass filtercoefficients, may or may not differ between these ACs.

A noise scan begins in step 30 with the initialization/power-up ofsensor circuit 1. In step 31, the sensor receive signal is obtained fromthe sensor 20 using the sensor interface 2, as discussed in thepreceding, without a stimulus signal being applied. The signal thus onlycomprises noise.

The sensor receive signal subsequently in step 32 is A/D converted usingthe A/D converter 5 to obtain a digital sensor receive signal. Duringthe noise scan, data is acquired at a frequency f_(b) which we denote asthe base frequency or predefined noise scan frequency. During aconfiguration step (not shown), f_(b) is chosen to be a common multipleof the SN-scan sampling frequencies of a multitude of ACs. Let one ofthese ACs, for example, have a candidate carrier frequency f_(c). Duringan SN-scan with this AC, the sampling frequency would be f_(s)=2·f_(c).The predefined noise scan frequency, however, is R times higher, namelyf_(b)=R·2·f_(c), where R is a decimation rate. The A/D converter 5 thussamples the analog sensor receive signal during the noise scan atsampling frequency f_(b)=2·R·f_(c), i.e., the sampling frequency is Rtimes higher than for the SN-scan.

In step 33, decimated digital receive signals are generated by thedecimation circuit of digital signal processing circuit 15 from thedigital sensor receive signal.

Decimation of the digital sensor receive signal reduces the number ofsamples in the respective decimated digital receive signal. FIG. 4schematically shows the operation of the digital signal processingcircuit 15 for exemplary decimation rates R=2, 3, 4, and 6.

The decimation uses multiple different decimation rates, namely as shownin FIG. 4, decimation rates R=2, 3, 4, and 6. For each decimation rate,multiple decimated digital receive signals are provided, which will bediscussed in more detail in the following.

The application of decimation with multiple decimation rates allows thatmultiple possible ‘candidate’ acquisition configurations can beevaluated from the same measurement data, i.e., the digital sensorreceive signal. As discussed in the preceding, the (candidate)acquisition configurations in this embodiment have sampling frequenciesof which the noise scan sampling frequency is a common multiple.Low-pass filter lengths and coefficient values may differ as well insome examples. Decimation of the noise scan digital sensor receivesignal with multiple decimation rates provides decimated digital receivesignals with these different sampling frequencies and thus makes itpossible to evaluate the different candidate acquisition configurationsusing the same sensor receive signal. As will be apparent from theexample in FIG. 4, while the scan duration is constant (namelyL^((i))=24 samples), the number of samples in the decimated digitalreceive signals, which is equal to the packet length L of the respectiveAC, varies depending on the decimation rate. In some embodiments, thescan duration for different ACs can be different. For example, if thenoise scan would yield 20 samples in total, R=4 would result to 4*5=20samples, but with R=3, there would only be 3*6=18 samples, because3*7=21 does not ‘fit’ into the original sample length of 20.

Once decimated digital receive signals are generated, in step 34, thedigital signal processing circuit 15 demodulates the decimated digitalreceive signals. This is conducted herein, without limitation, bymultiplication of the samples alternatingly with plus one and minus oneas it would also be done during an SN-scan. After demodulation, digitallow-pass filtering, e.g., using one or more finite impulse response(FTR) filters, removes unwanted high frequency signal components. It isnoted that different decimation rates R may require differences in thefurther processing, in particular, the number of filter coefficients ofthe FIR filters may be equal to the number L_(ρ) ^((i,j)) of samplesafter decimation, i.e. equal to the packet length L of the respectivecandidate AC, and the values of the filter coefficients may differ fordifferent decimation rates R accordingly. In the present embodiment,filtering is applied using a Hanning window of length L as the vector oflow-pass filter coefficients. The n-th element of the Hanning window, asdefined by Mathworks, is

${w_{n} = {\sin( \frac{\pi( {n + 1} )}{L + 1} )}},{0 \leq n \leq ( {L - 1} )}$

After the filtering, a further decimation by L_(ρ) ^((i,j)) is appliedto provide a single output value for a block of acquired ADC samples.The resulting digital processing chain of the digital signal processingcircuit 15 is discussed in more detail in the following with referenceto FIG. 5, where for simplicity L_(ρ) ^((i,j)) is abbreviated as L.

Evaluation is done in step 35 by the noise evaluation circuit 8 thatdetermines noise measures for the candidate acquisition configurationsfrom the decimated digital receive signals.

As mentioned in the preceding, for each decimation rate, a group ofdecimated digital receive signals is determined. For example, and asshown in FIG. 4, the top shows the original ADC 5 output signal withL^((i))=24 samples x_(k), k=0, 1, . . . , 23. Below it shows fordecimation rates R=2, 3, 4, 6 how the single original ADC signal isdemultiplexed into R signals with different starting samples x_(v), v=0,1, . . . , R−1. Hereby, the samples of the decimated signals are renamedas x_(n) ^((R,v))=x_(v+n·R). That is, for the exemplary values ofL^((i))=24 samples and R=2, 3, 4, 6 in FIG. 4, we yield decimatedsignals of lengths 12, 8, 6, and 4 samples, respectively.

As can be seen from FIG. 4, for decimation rate R=3, a total of threedecimated digital receive signals are determined, which show differentstarting phases, i.e., different starting samples. This is done tocalculate a particularly beneficial noise measure in step 35, namely an‘effective noise power estimate’, also referred to as ‘ENPE’.

Accordingly, the process of FIG. 3 provides that, in the digital domain,the digital receive signal is decimated using different signal phasesv∈{0, 1, . . . , R−1}, where each of the resulting R signals hassampling rate f_(s)=f_(b)/R. It is noted, that in some embodiments, theset of employed signal phases can also be a subset of the full set ofphases {0, 1, . . . , R−1}, for example {0, 2, 4, . . . , R−1}. In otherwords, each group of decimated digital receive signals does notnecessarily comprise all possible signal phases.

Mathematically, each decimation rate R is assigned a coefficient vectorwith the same length as the decimated signals, for example containingthe coefficients of an FIR low-pass filter (LPF). To compute an ENPE fora decimation rate R, for each of the up to R decimated signal vectorsthe dot product with the assigned coefficient vector is computed in step35 by noise evaluation circuit 8. Optionally and in some embodiments,these dot products may be normalized by dividing by the sum of allcoefficients. Then the average of the squared normalized dot products iscomputed to yield the ENPE.

In mathematical terms, FIG. 4 shows how for each R∈{2,3,4,6} theoriginal signal vector x=[x₀×₁×₂ . . . x₂₃] is split into up to R signalvectors

$x^{({R,v})} = {\lbrack {x_{v}x_{v + R}x_{v + {2R}}\mspace{20mu}\ldots\mspace{20mu} x_{v + {{({\frac{L}{R} - 1})} \cdot R}}} \rbrack = \lbrack {x_{0}^{({R,v})}x_{1}^{({R,v})}x_{2}^{({R,v})}\mspace{20mu}\ldots\mspace{14mu} x_{\frac{L}{R} - 1}^{({R,v})}} \rbrack}$

where we denote x_(n) ^((R,v))=x_(v+n·R), and v∈{0, 1, . . . , R−1}. Letw=[w₀ w₁ w₂ . . . w_(N)] denote the coefficient vector of length(N+1)=L^((i))/R which is assigned to each decimation rate R. The ENPEη(x, R, w) for a receive signal at carrier frequency f_(c) which issampled at f_(s)=2·f_(c), demodulated and filtered with the coefficientsis then computed from the noise scan data vector x sampled at basefrequency f_(b)=R·2·f_(c), decimation rate R and coefficient vector w as

${\eta( {x,R,w} )}:={\frac{1}{R} \cdot {\sum\limits_{v = 0}^{R - 1}{( {\frac{1}{\sum\limits_{n = 0}^{N}w_{n}} \cdot {\sum\limits_{n = 0}^{N}{x_{{n \cdot R} + v} \cdot ( {- 1} )^{n} \cdot w_{n}}}} )^{2}.}}}$

Hereby, the term

$( {{\frac{1}{\sum\limits_{n = 0}^{N}w_{n}} \cdot \Sigma_{n = 0}^{N}}{x_{{n \cdot R} + v} \cdot ( {- 1} )^{n} \cdot w_{n}}} )^{2}$

is referred to as phase-instantaneous noise measure. The normalizationterm

$\frac{1}{\sum\limits_{n = 0}^{N}w_{n}}$

ensures a filter DC gain of 1 and can be moved out of the sum over thephases v—then being squared—or can be considered in a later processingstep, leaving

${\eta^{\prime}( {x,R,w} )}:={\frac{1}{R} \cdot {\sum\limits_{v = 0}^{R - 1}{( {\sum\limits_{n = 0}^{N}{x_{{n \cdot R} + v} \cdot ( {- 1} )^{n} \cdot w_{n}}} )^{2}.}}}$

To distinguish the different decimation rates R, we assign a superscriptwith index j=0, 1, 2, . . . for the j-th decimation rate R^((0,j)).Likewise, we do for the coefficient vector assigned to decimation rateR^((0,j)), yielding w^((0,j)).

Because the same measurement data is used to compute noise measures fordifferent candidate ACs, temporal changes experienced, for example, withamplitude modulated noise do affect the noise measures, but the noisemeasures computed from the same data still remain comparable to reliablyidentify the AC with the relatively lowest noise measure.

For decimation rates which are a multiple of two, computationalcomplexity can be reduced by changing the sum over the phases v=0, 1, .. . , R−1 into the sum over the phases v=v₀, v₀+R/2 where v₀∈{0, 1, . .. , R/2−1}. For example, for R=6, one can employ

${{\eta^{''}}^{({x,6,w})}:={\frac{1}{6} \cdot {\sum\limits_{{v = v_{0}},{v_{0} + 3}}\;( {\frac{1}{\sum\limits_{n = 0}^{N}w_{n}} \cdot {\sum\limits_{n = 0}^{N}{x_{{n \cdot 6} + v} \cdot ( {- 1} )^{n} \cdot w_{n}}}} )^{2}}}},$

v₀∈{0,1,2}

to compute a complexity-reduced ENPE.

Once the noise measures, i.e., the ENPEs herein, are determined for eachcandidate acquisition configuration, the ENPEs are passed toconfiguration circuit 9, which selects the acquisition configuration foroperation of the sensor system from the candidate acquisitionconfigurations using the determined ENPEs in step 36.

In this embodiment, the configuration circuit 9 determines in step 36,which of the candidate acquisition configurations yields the lowestnoise by evaluating the associated ENPEs.

Once a candidate acquisition configuration is selected as acquisitionconfiguration, the noise scan is complete. The acquisition configurationis provided to drive circuit 4 by the configuration circuit 9. Inaddition, the selected acquisition configuration is stored in memory 10for future reference. The capacitive touch sensing system 21 is thenoperated in at least one SN-scan (step 37) according to the results ofthe noise scan. It is noted that an SN-scan may be conducted formultiple sensor (transmit) lines 3, particularly in case ofmutual-capacitance sensors. After the SN-scan(s), a new noise scan isconducted, beginning with step 30.

The two resulting signal processing chains for the noise scan and theSN-scan are shown in FIG. 5 in a simplified and schematic diagram.

In the top, FIG. 5 shows the digital processing for data acquired duringan SN-scan. The sensor receive signal is converted from the analog todigital domain at twice the carrier frequency f_(c), i.e. f_(s)=2·f_(c),using the ADC 5 to obtain the digital sensor receive signal. The digitalADC output signal, i.e. the digital sensor receive signal, is thenprovided to the digital signal processing circuit 15, which comprises ademodulator 13, an FIR low pass filter 6, and a decimation circuit 7.The digital ADC output signal, i.e. the digital sensor receive signal,is demodulated by the demodulator 13 by multiplying its samplesalternatingly with plus and minus one, and the demodulated signal isinput into the digital low-pass LPF filter 6 with L filter coefficientsand finally decimated with factor L, i.e., only one sample is output ofthe decimator 7 after inputting L samples.

In the bottom part of FIG. 5, the processing of the digital processingcircuit 15 and the noise evaluation circuit 8 during the noise scan isshown in more detail. The ADC 5 is sampling the analog sensor receivesignal at the predefined noise scan frequency. In FIG. 5, the processingof one exemplary AC is shown. The operation would be conducted for eachAC to be considered.

The exemplary AC has a carrier frequency f_(c)=f_(b)/(2·R). The sampledsignal after conversion to obtain the digital sensor receive signal byADC 5, is demultiplexed onto R signals indexed with v∈{0, 1, . . . ,R−1}, where each of the R signals has sampling rate f_(s)=2·f_(c).Comparable to the processing during the SN-scan and to provideconditions, similar to those in an SN-scan, each of the demultiplexedsignals is demodulated by a respective demodulator 13 by multiplying itssamples alternatingly with plus and minus one, and each demodulatedsignal is being filtered in an FIR low-pass filter LPF 6 and decimatedby decimation circuit 7. After analog-to-digital conversion andprocessing R·L samples x_(k), for each decimated signal we have obtainedone decimated sample. Each decimated sample is squared by noiseevaluation circuit 8 and then the average of these R squared samples iscomputed by noise evaluation circuit 8, yielding an ENPE.

It is noted that the processing, discussed with reference to FIGS. 3 and5 in the preceding, does not necessarily need to be completed ‘online’.Instead, and as discussed in the preceding with reference to FIGS. 3-5,where each ADC sample x_(k) may be discarded as soon as it has beenmultiplied with (±1) yielding the demodulated value as an intermediateproduct, in an embodiment, the samples x_(k) may be stored in memory 10for offline processing. In this embodiment, the processing, discussedwith reference to FIGS. 3 and 5, is initiated after A/D conversion.

FIG. 6 shows an exemplary flow diagram of the operation of sensorcircuit 1 in another embodiment. The operation corresponds to thepreceding discussion, in particular referring to FIG. 3. Accordingly theoperation in steps 60-67 corresponds to the operation in respectivesteps 30-37, except for step 66 a, in which configuration circuit 9 setsthe aperture time of the acquisition configuration that is used by drivecircuit 4 for the SN-scan, to an integer multiple of the aperture time(including identical aperture times, i.e. where the integer=1), used byA/D converter 5 during the current noise scan. To do so, configurationcircuit 9 is connected to A/D converter 5 (not shown in FIG. 1). Theaperture time is set back to the original aperture time in step 60 uponthe next noise scan cycle.

The present embodiment is based on the inventor's recognition that, whencapturing analog data to create a time-discrete sample, the timeduration for which the analog signal is input to the measurement system,i.e., the time during which the measurement system is exposed to theoutside world and thus its internal analog state is changed by theanalog input signal, can affect the output sample's value. For ADC 5this time duration is the so-called ‘aperture time’. The schematicdiagram of FIG. 7 shows the magnitude of an ideal ADC's transferfunction, also referred to as susceptibility to single-tone signals withfrequency f_(n), for aperture times 0.833 us and 2.5 us. Spectral zeroscan be observed at multiples of the inverse aperture times, i.e.,1/0.833 us=1.2 MHz and 1/2.5 us=400 kHz, respectively.

With some touch sensing devices, upon sensing an electrode, anelectrical current flowing to or from a sensor electrode is beingintegrated for a deterministic amount of time. This integration timealso is considered to be an aperture time.

The aperture time cannot be longer than the time between two successivesamples, the sample interval, because the aperture time windows of twosuccessive samples cannot overlap. The higher the sampling frequency,the shorter the sample interval and thus the shorter the maximumaperture time. Hence, when sampling at the predefined noise scanfrequency f_(b)=2·R·f_(c), where f_(c) is the carrier frequency of anexemplary AC, the maximum aperture time 1/(2·R·f_(c)) is shorter thanduring an SN-scan where the sampling frequency is 1/(2·f_(c)).

A desired aperture time may also depend on the sensor type at hand. Forexample, signal settling times are typically higher for ITO sensors thanfor PCB sensors due to the lower conductivity of ITO compared to copper.Therefore, a longer aperture time may be desired for an ITO sensorcompared to a similarly shaped PCB sensor. It is noted that there arealso cases where the aperture time has a practically negligible effectonto the measurement values. These may include, for example, voltagemeasurements done on the output of a voltage follower circuit (‘bufferamplifier’).

It is however possible in certain scenarios that a desired aperture timeis shorter than the SN-scan sample interval but exceeds the noise scansample interval. Then, obviously, the desired aperture time is notapplicable to the noise scan. A different, shorter aperture time may bechosen for the noise scan. Choosing different aperture times for SN-scanand noise scan may however possibly compromise the potential to yield areliable ENPE from noise scan data for an SN-scan. Particularly, whenthe noise scan susceptibility spectrum has zeros at frequencies wherethe SN-scan susceptibility spectrum does not, it is possible thatharmful noise is not being seen in noise scan data and a noiserobustness algorithm may make insensible decisions.

For certain ratios between SN-scan and noise scan aperture times,however, it is possible to yield a relatively best carrier frequencydecision, i.e., decision about a relatively best acquisitionconfiguration for some noise scenarios. This is the case when the noisescan aperture time is an integer fraction of the SN-scan aperture timeor correspondingly, when the SN-scan aperture time is an integermultiple of the noise scan aperture time. This is shown by way ofexample in FIG. 7 for the fraction ⅓ when all ‘noise-scan zeros’(integration time 0.833 us) fall onto ‘SN-scan zeros’ (integration time2.5 us).

The ENPE provides an absolute estimate for the noise power of a receivedsignal after demodulation and low-pass filtering. For some sensorsystems or applications there may be an upper threshold for this noisepower above which operation is not desirable.

One exemplary approach to yield a lower noise power is to increase thenumber L of acquired and processed samples, denoted herein the ‘packetlength’, and thus the filter length equal to L. Note that the filterlength is equal to the filter order N plus one, i.e. L=N+1. However,increasing the packet length alone and by itself does not generallyimprove noise suppression. Noise suppression is dependent primarily onthe chosen low-pass filtering of which the packet and filter length isonly one aspect. FIG. 17 shows an example of the spectral noisesuppression in case the packet size is increased from 5 to 7 samples forboxcar window and Hanning window. For example, in the top plot withboxcar window, the noise susceptibility is increased for the normalizedfrequency

$\Omega:={\frac{2\;\pi\; f}{f_{s}} = {0.4\pi}}$

radians/sample, not decreased.

FIG. 9 shows for boxcar or rectangular window low-pass filters (top) and‘hanning’ window low-pass filters (bottom) how the packet length needsto be increased such that noise suppression is improved for all noisefrequencies f=f_(n), or all normalized frequencies

$\Omega = \frac{2\;\pi\; f}{f_{s}}$

in FIG. 9. Particularly, spectral zeros for shorter packet lengthsshould fall onto zeros for longer packet lengths. In FIG. 9 it is shownthat this is achieved when, for a boxcar window LPF, the longer packetlength is a multiple of a shorter packet length, and for a Hanningwindow LPF the longer packet length is a multiple of a shorter packetlength plus one. For boxcar, Hann window, and Matlab's Hanning window (aHanning window herein corresponds to a Hann window with the first andlast sample removed) low-pass filters the rule how to increase a packetlength L to L′ in order to guarantee improved noise suppression for allnoise frequencies is

$L^{\prime} = \{ {\begin{matrix}{{k \cdot L}\text{:}} & {\ {{boxcar}\mspace{14mu}{window}}} \\{{k \cdot L} - {( {k - 1} )\text{:}}} & {{Hann}\mspace{14mu}{window}} \\{{k \cdot L} + ( {k - {1\text{:}}} } & {{‘{hanning}’}\mspace{14mu}{window}}\end{matrix},{k = 1},2,3,\ldots} $

Another requirement for sensor systems may be a minimum report rate,i.e., capacitive touch or touch-less sensing system 21 may be requiredto output estimated data at a report rate equal to, or higher than, aminimum report rate. This estimated data can, for example, be low-passfiltered and decimated data as is illustrated in FIG. 5 (top) as “totouch detector 11”, or data computed therefrom. Such a minimum reportrate typically is independent of how the reported data is acquired andprocessed, that is, it is, for example, independent of the carrierfrequency. But the minimum report rate sets the upper limit for themeasurement time to the inverse of the minimum report rate. Anotherrequirement for capacitive touch sensing system 21 may be a minimum SNR,or in other words that the expected noise power of an output value isbelow a limit. In some embodiments, this may even be the primaryrequirement, and when it cannot be fulfilled with a desired report rate,then the report rate is reduced (i.e., the scan is time increased) whilemaintaining—and trying to meet—the noise power limitation, as isdiscussed in the following with reference to FIGS. 8A and 8B.

FIGS. 8A and 8B show a flow diagram of the operation of sensor circuit 1in another exemplary embodiment. The operation corresponds to thepreceding discussion, in particular referring to FIG. 6. Accordingly,the operation in steps 80-87 corresponds to the respective operation insteps 60-67, except for steps 82 a and 86 a-86 g, as discussed in thefollowing.

In step 82, the sensor receive signal, obtained from the capacitivetouch sensing system 21 is A/D converted to obtain the digital receivesignal, which corresponds to the processing, discussed in the precedingwith reference to steps 32 and 62. In the present embodiment, the sensorreceive signal obtained during step 81 has a maximum predefined scantime, i.e., a predefined maximum duration. For example, the predefinedmaximum duration may be 200 microseconds.

In step 82 a, a copy of the digital receive signal with the maximum scantime is stored in memory 10. Then, a portion of the digital receivesignal, namely with a predefined minimum scan time, is selected. Thefurther processing of steps 83-85 is based on this portion of thedigital receive signal.

In step 86, the acquisition configuration is selected from the candidateacquisition configurations. For clarity, the processing in step 86 isshown in FIG. 8B broken down in steps 86 a-86 g.

In step 86 a, the configuration circuit 9 selects the candidateacquisition configuration that yields the lowest noise by evaluating theassociated ENPEs, as determined in step 85. In step 86 b, theconfiguration circuit 9 determines, if the selected ENPE meets or islower than a predefined noise threshold, which may be defined as noisepower or an SNR. For example, the predefined noise threshold withrespect to SNR may be of 20 dB. If the selected ENPE meets or is lowerthan the predefined noise threshold, the selected candidate acquisitionconfiguration is set to be the acquisition configuration for the SN-scanin step 87, corresponding to the preceding explanation. The aperturetime for the SN-scan is set in step 86 c as discussed with reference toFIG. 6.

In case the noise measure for the selected candidate acquisitionconfiguration exceeds the predefined noise threshold, the processingcontinues with step 86 d. Assuming that in step 86 d, the maximumpredefined scan time has not been reached, the configuration circuit 9increases the scan time by approximately an integer multiple andevaluates this increased scan time. To do so, configuration circuit 9 instep 86 e obtains the copy of the original digital receive signal withthe maximum scan time from memory 10, which was stored in step 82 a.Then, a larger portion of original digital receive signal is selected instep 86 f, having a scan time that is an integer multiple of theprevious scan time, e.g. double the scan time of the preceding portionthat was evaluated. The processing then is continued in step 83 and theincreased scan time is evaluated according to steps 83-86, as discussedbefore.

Mathematically, the Noise Robustness Level (NRL) is used herein as anindex for a predefined maximum scan or measurement time. For example,let NRL ρ=0 denote the lowest NRL corresponding to the shortest maximumscan time T₀. For each candidate acquisition configuration, its packetlength is set to the maximum number └T₀·f_(s)┘ of samples that can beacquired during this time with sampling frequency f_(s)=2·f_(c), wheref_(c) is the AC's carrier frequency. For example, when T₀=125 μs andf_(c)=100 kHz, then the resulting packet length is [125 μs·100 kHz]=12ADC samples.

For the next higher NRL ρ=1, for each AC the packet length is determinedaccording to Equation (1) depending on the low-pass filter design, forexample with parameter k=2, i.e. approximately doubling the scan time.

The discussed steps are repeated in an iterative fashion until either anacquisition configuration is found that meets the noise threshold or themaximum predefined scan time is reached and no acquisition configurationmeets the noise threshold. In the latter case, the query of step 86 dleads to the generation of a warning signal at output 12 in step 86 g,warning that no suitable acquisition configuration was found. Theoperation then proceeds to step 86 c using the AC yielding the bestnoise measure for operation in the SN-scan.

As will be apparent from the preceding, a scan cycle may consist of anoise scan followed by an SN-scan using the AC which yielded the bestnoise measure. Then follows the next scan cycle with the next noise scanand SN-scan. The scan cycle then is repeated until the device is shutdown.

As discussed in the preceding, the goal is to find the lowest NRL, i.e.,the shortest required scan time and thus highest report rate, for whichthere is a candidate acquisition configuration yielding an ENPE of atmost the noise threshold. When there are more than one acquisitionconfiguration with the same scan time yielding an ENPE below the limit,the process of FIGS. 8A and 8B selects the AC yielding the lowest ENPE.

When there are candidate ACs whose sampling frequencies do not share acommon multiple, a slightly modified process may be employed that usesmultiple predefined noise scan frequencies. A corresponding exemplaryembodiment is shown in the flow diagram of FIG. 10.

Given a noise scan signal sampled at the predefined noise scan frequencyf_(b), it is possible to choose a multitude of different values for theinteger decimation rate R.

However, the number of carrier frequencies

$f_{c} = \frac{f_{b}}{2\; R}$

for which an ENPE can be computed given a signal sampled at noise scanfrequency f_(b) is practically limited.

To increase the set of candidate carrier frequencies, additional noisescan frequencies can be evaluated in an according embodiment. Todistinguish these noise scan frequencies, we assign a superscript withindex i=0, 1, 2, . . . for the i-th candidate base frequency f^((i)).The j-th decimation rate for the i-th candidate base frequency isdenoted as R^((i,j)), and its corresponding candidate carrier frequencyand coefficient vector are denoted as f^((i,j)) and w^((i,j)),respectively.

We denote L_(ρ) ^((i,j)) the packet length for the AC with basefrequency index i, sub-frequency index j and NRL ρ.

The process begins in step 100 with the initialization of sensor circuit1. For each predefined noise scan frequency, an individual noise scan isconducted in steps 101, 102, and 103. It is noted that the presentembodiment is not limited to the conduction of three subsequent noisescans. The operation during each of the noise scans corresponds to oneof the embodiments, discussed in the preceding with reference to FIGS.1-9. In each step 101, 102, and 103, a noise measure for at least onecandidate AC is obtained. In some embodiments, noise measures for thesame candidate AC may be obtained in a multitude of steps 101, 102, and103.

In step 104, an overall acquisition configuration is determined from thecandidate acquisition configurations evaluated in the steps 101, 102,and 103. The overall acquisition configuration is determined byselecting the candidate acquisition configuration of steps 101, 102, and103 for which the lowest ENPE is yielded overall. In other words, theoverall acquisition configuration corresponds to the best possiblecandidate acquisition configuration of the noise scans 101, 102, 103.The idea of NRLs can also be applied for this case of multiple noisescan frequencies. In step 105, the sensor system is operated in anSN-scan using the overall acquisition configuration. The operation thenreverts to step 100 until the processing of sensor circuit 1 is stopped.

As opposed to other known approaches, the approach as describedaccording to the various embodiments not only provides a solution foridentifying a relatively best carrier frequency, but a complete solutionfor noise robustness. It even yields robustness to, for example, AMnoise and square noise. This is possible due to the highly accurate,quantitative SNR or noise power estimates which can be computed from thesame measurement data but for different ACs. This further allows forfinding a trade-off between touch report rate and output SNR.

Furthermore, for a selected low-pass filter design method, for example aboxcar window filter function, and with the requirement to assureimproved noise robustness when increasing the scan time while leavingother AC parameters unchanged, many of the candidate ACs' parameters(such as, e.g., filter length and filter coefficient values) can bederived from few high-level requirements (such as, e.g., a 200 us scantime), allowing for a simple noise robustness configuration without theneed for intense training.

A further exemplary aspect of this disclosure relates to obtainingdecoupled copies of electric currents as well as digital processing forsignal acquisition with overlapping aperture windows.

When capturing analog data to create a time-discrete or digital outputsample, the time duration for which the analog signal is input to themeasurement system, i.e., the time during which the measurement systemis exposed to the outside world and thus its internal analog state ischanged by the analog input signal, and can affect the output sample'svalue.

For an analog-to-digital converter (ADC) this time duration is known asthe aperture time, as discussed in the preceding. To recall, FIG. 7shows the magnitude of an ideal ADC's transfer function, also referredto as susceptibility to single-tone signals with frequency f_(n), foraperture times 0.833 us and 2.5 us. We observe spectral zeros atmultiples of the inverse aperture times, e.g. 1/0.833 us=1.2 MHz and1/2.5 us=400 kHz, respectively.

With some available touchscreen controllers, upon sensing an electrode,an electrical current flowing to, or from, a sensor electrode isintegrated for a deterministic amount of time to measure the amount ofelectric charge moved during this time. This integration time is anaperture time. A basic exemplary diagram for charge measurement usingcurrent integration is shown in FIG. 11. It shows an unknown currentsource generating current i_(in) which is integrated on capacitorC_(int) while the aperture switch controlled with the signal s_(ap) (t)illustrated in the right-hand side of the figure is on and the resetswitch controlled with the signal s_(res)(t) is off. The resistor R ofthe current source is negligible when the aperture switch is on.

With standard serial processing of the analog signal, the aperture timetypically cannot be longer than the time between two successive samples,the sample interval, because the aperture time windows of two successivesamples cannot overlap. The higher the sampling frequency, the shorterthe sample interval and thus the shorter the maximum aperture time.

There are applications where it may be beneficial to have adjacent oroverlapping aperture time windows for successive samples. For example,in the preceding, two different types of measurements where the samplingfrequency of the first type is a multiple of the sampling frequency ofthe second type is described, namely the ‘noise scan’ and the ‘SN scan’,yet the same aperture time is desired for both. While the aperture timeis chosen for the SN scan, the sampling frequency for the noise scan maybe too high to fit an aperture window of the chosen time between twosuccessive samples—the aperture windows would overlap.

To yield overlapping aperture time windows, some means of parallelprocessing may be beneficial. For example, for systems like thementioned touchscreen controllers, two or more integrators would bebeneficial. A problem may be the risk that these two or moreintegrators, when tapping the same pad or measurement node, maypotentially mutually interfere their measurements. This is illustratedin FIG. 12, where on the right-hand side the states s_(ap) ⁽⁰⁾(t) ands_(ap) ⁽¹⁾(t) of the aperture switches are plotted over time. During thetime when both aperture switches s_(ap) ⁽⁰⁾=s_(ap) ⁽¹⁾=1 are on, theunknown input current is split uncontrolled between the two integrators.Hence, deterministic measurement with overlapping aperture time windowsmay not be possible. The same analog input current cannot be measuredmultiple times this way without the measurements interfering each other.

In capacitive sensing, a desired aperture time may, e.g., depend on thesensor type at hand. For example, signal settling times are typicallyhigher for ITO sensors than for PCB sensors due to the lowerconductivity of ITO compared to copper. Therefore, a longer aperturetime may be desired for an ITO sensor compared to a similarly shaped PCBsensor.

Based on the preceding, a solution may be to employ a current amplifierwith one input and multiple outputs to yield a multitude of decoupledcopies of the input current. Each copy may then be tapped with oneintegrator, and the integrator input currents are decoupled, i.e.,mutually independent. In a digital post-processing step, the dataobtained from the multitude of analog copies may, e.g., be rearranged toyield a single digital output signal.

The principle approach of the present discussion is to create multipledecoupled copies of an analog input signal. Then, analog processing andA/D conversion may be performed for each of the signal copiesindividually. The final step is to interleave, or multiplex, the digitalsamples from the different processing branches into a single outputsignal.

A standard electronic component where an input current is independentfrom an output current is a transistor. For more complex components likeamplifiers which can contain such transistors, this independence holdstoo. When an input current controls two output currents, and the inputcurrent is independent of either output current, this implies that theoutput currents are mutually independent from each other too.

For some touchscreen controller devices and classical touchscreencontroller measurements, the analog input signal is an electric current.Some existing touchscreen controller's analog front end (AFE) providesmultiple, essentially identical parallel units for analog processingwhich are called slices. Each slice comprises an integrator.

While it would be desirable to have fully independent timings fordifferent integrators, some touchscreen controller devices may berestricted to a common sampling interval or sampling frequency for allslices. Apart from a required small digital modification, the existingdevices, however, would allow independent measurements of two copies ofan input current, where the aperture time windows of the twomeasurements do overlap. FIG. 13 schematically shows two of theso-called slices of an exemplary AFE of a touchscreen controller. Thepad of the main slice in the top left of FIG. 13 is connected to theinput X of a current amplifier. A non-inverting output Z0 of thiscurrent amplifier is connected to an integrator whose output isconnected to an ADC. An inverting output Z1 of the main slice's currentamplifier is connected to the input of an integrator on a secondaryslice, again followed by an ADC. The second slice's current amplifier isdisconnected such that only the main slice's amplifier inverted currentis input to the integrator. While the aperture switches INTMOE can becontrolled independently for main and secondary slice, the integratorreset switches RST1 and RST 2 may not be controllable independently.

In the preceding, a need for overlapping aperture time windows, orcurrent integration windows, has been discussed for the noise scan. Forsuch a noise scan, one may be primarily interested in the measurementdata from a single slice, for example a slice connected to a sensorelectrode where a highest noise level may be expected. Assuming that amain slice has been connected to this noisiest electrode, for examplethis noisiest electrode is connected to the pad of the Main Slice inFIG. 13, then theoretically, two decoupled copies of the main slice'sinput current are obtained, and on both the main and secondary slice, itis possible to open or close the aperture or reset switches withoutaffecting the current on the respective other slice.

FIG. 14 shows an exemplary timing diagram for current integration andintegrator resetting when assuming slice-independent control of apertureand reset switches. Each integration window is preceded by a reset ofthe integration capacitor. The integration windows of the main andsecondary slice are interleaved and overlapping in time. Afteranalog-to-digital (A/D) conversion, the samples from the two slices areinterleaved to yield a single digital signal. For example, the newsingle digital signal is created by concatenating the first outputsample from the main slice, the first output sample from the secondaryslice, the second sample from the main slice, the second sample from thesecondary slice, and so on. Note that in the context of a noise scan,the obtained signal is decimated before further processing, and afterdecimation the current integration windows corresponding to successivesamples in these decimated signals are no longer overlapping.

However, while integration can be controlled for main and secondaryslices separately, the timing of FIG. 14 may be not realizable with sometouchscreen controller devices because of an integrator reset controlwhich is common for main and secondary slices.

What can be done with some touchscreen controllers is a timing similarto that in FIG. 14, but with non-overlapping integration windows, as isillustrated in FIG. 15. In fact, A/D conversion also is conductedsynchronously on the main and secondary slices, as indicated by verticaldashed lines, such that every other digital sample from each slice isundesired—because it is acquired not at the end of the currentintegrators' integration phase but during a possibly random integratorstate—and thus may be discarded.

Data obtained with a test implementation using the timing configurationof FIG. 15 is shown in FIG. 16. A single-tone signal with 20 kHz iscoupled into a sensor electrode connected to a slice Y34, and thesampling frequency is 200 kHz. The samples from the main slice Y34 and asecondary slice Y35 are shown in an interleaved manner, while the solidand dashed lines connect the samples from each slice, respectively. Itcan be observed that the signal of slice Y35 (dashed line) still needsto be re-inverted and shifted, as the signal for Y35 is approximately amirror image of the signal for Y34 mirrored at the level of ADC value−15. The required offset would need to be determined (for example, withthe pad/electrode disconnected, i.e., no input signal) before the actualsignal acquisition, however, signal reconstruction in the digital domainis feasible.

When referring to a ‘copy’ of an analog signal herein, an exactone-to-one copy is not necessarily required. For some applications, astrictly monotonic copying function may be sufficient, and anydistortion may be compensated for in the digital domain.

For systems with processing as in touchscreen controller devices where acurrent is being integrated before A/D conversion, however, only alinear distortion of the input signal, i.e., the input current, may beacceptable in some embodiments to allow digital equalization (i.e.,compensation of the distortion). Also, in general, a more or less linearcopying function can be beneficial, for example, when considering signalequalization together with ADC quantization noise.

The preceding touchscreen controller specific solution allows foroverlapping aperture time windows when the acquisition frequency on mainand secondary slices are the same but only the acquisition phasediffers. However, when hardware control would allow fully independenttiming for different slices, given multiple copies of the same analogsignal, it would be possible to yield a generic solution to the problemof signal acquisition for noise level evaluation with different AFEconfigurations, including arbitrary different sampling frequencies andaperture time windows.

Some embodiments of a sensor system with an analog input signal x(t)provides that the sensor system makes two or more analog copiesy_(i)(t), i=0, 1, . . . of x(t).

In some embodiments, the copy y_(i)(t) is a strictly monotonic functionof x(t).

In some embodiments, the copy y_(i)(t) is a linear functionsy_(i)(t)=b_(i)*x(t)+a_(i) of x(t).

In some embodiments, the sensor system is a capacitive sensing system.

In some embodiments, the signal x(t) is an electric current.

In some embodiments, the signal y(t) is an electric current.

In some embodiments, two or more analog signal copies y_(i)(t) are inputto an analog circuit Hi for generating digital samples and the aperturewindows of at least two circuits Hi overlap in time.

In some embodiments, the analog circuits Hi comprise an integrator.

In some embodiments, the sampling frequency on two or more circuits Hiis the same.

In some embodiments, the sensor system comprises a current amplifierwhose input is fed with x(t) and where the current amplifier has two ormore output stages sharing one input stage.

In some embodiments, samples from signals on different branches aremultiplexed yielding a single output signal.

The generic solution for making copies of an analog input signal toyield decoupled signals for independent processing enabled herein solvesthe problem of comparing any AFE configurations with each other and isbeneficial for finding a suitable acquisition configuration.

In some embodiments, the aperture time is increased beyond the samplingperiod, thus allowing a highly accurate noise power estimation.

As compared to an alternative approach of evaluating signals fromdifferent sensor electrodes, for the discussed approach there is no riskthat noise is coupled into the different sensor electrodes withdifferent coupling intensities, which could give wrong bias to theestimates-simply because of the discussed approach where all dataevaluated originates from a single sensor electrode.

Although the invention has been described with respect to specificembodiments thereof, these embodiments are merely illustrative, and notrestrictive of the invention. The description herein of illustratedembodiments of the invention, including the description in the Abstractand Summary, is not intended to be exhaustive or to limit the inventionto the precise forms disclosed herein (and in particular, the inclusionof any particular embodiment, feature or function within the Abstract orSummary is not intended to limit the scope of the invention to suchembodiment, feature or function). Rather, the description is intended todescribe illustrative embodiments, features and functions in order toprovide a person of ordinary skill in the art context to understand theinvention without limiting the invention to any particularly describedembodiment, feature or function, including any such embodiment featureor function described in the Abstract or Summary. While specificembodiments of, and examples for, the invention are described herein forillustrative purposes only, various equivalent modifications arepossible within the spirit and scope of the invention, as those skilledin the relevant art will recognize and appreciate. As indicated, thesemodifications may be made to the invention in light of the foregoingdescription of illustrated embodiments of the invention and are to beincluded within the spirit and scope of the invention. Thus, while theinvention has been described herein with reference to particularembodiments thereof, a latitude of modification, various changes andsubstitutions are intended in the foregoing disclosures, and it will beappreciated that in some instances some features of embodiments of theinvention will be employed without a corresponding use of other featureswithout departing from the scope and spirit of the invention as setforth. Therefore, many modifications may be made to adapt a particularsituation or material to the essential scope and spirit of theinvention.

Reference throughout this specification to “one embodiment”, “anembodiment”, or “a specific embodiment” or similar terminology meansthat a particular feature, structure, or characteristic described inconnection with the embodiment is included in at least one embodimentand may not necessarily be present in all embodiments. Thus, respectiveappearances of the phrases “in one embodiment”, “in an embodiment”, or“in a specific embodiment” or similar terminology in various placesthroughout this specification are not necessarily referring to the sameembodiment. Furthermore, the particular features, structures, orcharacteristics of any particular embodiment may be combined in anysuitable manner with one or more other embodiments. It is to beunderstood that other variations and modifications of the embodimentsdescribed and illustrated herein are possible in light of the teachingsherein and are to be considered as part of the spirit and scope of theinvention.

In the description herein, numerous specific details are provided, suchas examples of components and/or methods, to provide a thoroughunderstanding of embodiments of the invention. One skilled in therelevant art will recognize, however, that an embodiment may be able tobe practiced without one or more of the specific details, or with otherapparatus, systems, assemblies, methods, components, materials, parts,and/or the like. In other instances, well-known structures, components,systems, materials, or operations are not specifically shown ordescribed in detail to avoid obscuring aspects of embodiments of theinvention. While the invention may be illustrated by using a particularembodiment, this is not and does not limit the invention to anyparticular embodiment and a person of ordinary skill in the art willrecognize that additional embodiments are readily understandable and area part of this invention.

Any suitable programming language can be used to implement the routines,methods or programs of embodiments of the invention described herein,including C, C++, Java, assembly language, without limitation. Differentprogramming techniques can be employed such as procedural or objectoriented. Any particular routine can execute on a single computerprocessing device or multiple computer processing devices, a singlecomputer processor or multiple computer processors. Data may be storedin a single storage medium or distributed through multiple storagemediums, and may reside in a single database or multiple databases (orother data storage techniques). Although the steps, operations, orcomputations may be presented in a specific order, this order may bechanged in different embodiments. In some embodiments, to the extentmultiple steps are shown as sequential in this specification, somecombination of such steps in alternative embodiments may be performed atthe same time. The sequence of operations described herein can beinterrupted, suspended, or otherwise controlled by another process, suchas an operating system, kernel, etc. The routines can operate in anoperating system environment or as stand-alone routines. Functions,routines, methods, steps and operations described herein can beperformed in hardware, software, firmware or any combination thereof.

Embodiments described herein can be implemented in the form of controllogic in software or hardware or a combination of both. The controllogic may be stored in an information storage medium, such as acomputer-readable medium, as a plurality of instructions adapted todirect an information processing device to perform a set of stepsdisclosed in the various embodiments. Based on the disclosure andteachings provided herein, a person of ordinary skill in the art willappreciate other ways and/or methods to implement the invention.

It is also within the spirit and scope of the invention to implement insoftware programming or code any of the steps, operations, methods,routines or portions thereof described herein, where such softwareprogramming or code can be stored in a computer-readable medium and canbe operated on by a processor to permit a computer to perform any of thesteps, operations, methods, routines or portions thereof describedherein. The invention may be implemented by using software programmingor code in one or more general purpose digital computers, by usingapplication specific integrated circuits, programmable logic devices,field programmable gate arrays, and so on. Optical, chemical,biological, quantum or nanoengineered systems, components and mechanismsmay be used. In general, the functions of the invention can be achievedby any means as is known in the art. For example, distributed, ornetworked systems, components and circuits can be used. In anotherexample, communication or transfer (or otherwise moving from one placeto another) of data may be wired, wireless, or by any other means.

A “computer-readable medium” may be any medium that can contain, store,communicate, propagate, or transport the program for use by or inconnection with the instruction execution system, apparatus, system ordevice. The computer readable medium can be, by way of example only butnot by limitation, an electronic, magnetic, optical, electromagnetic,infrared, or semiconductor system, apparatus, system, device,propagation medium, or computer memory. Such computer-readable mediumshall generally be machine readable and include software programming orcode that can be human readable (e.g., source code) or machine readable(e.g., object code). Examples of non-transitory computer-readable mediacan include random access memories, read-only memories, hard drives,data cartridges, magnetic tapes, floppy diskettes, flash memory drives,optical data storage devices, compact-disc read-only memories, and otherappropriate computer memories and data storage devices. In anillustrative embodiment, some or all of the software components mayreside on a single server computer or on any combination of separateserver computers. As one skilled in the art can appreciate, a computerprogram product implementing an embodiment disclosed herein may compriseone or more non-transitory computer readable media storing computerinstructions translatable by one or more processors in a computingenvironment.

A “processor” includes any, hardware system, mechanism or component thatprocesses data, signals or other information. A processor can include asystem with a general-purpose central processing unit, multipleprocessing units, dedicated circuitry for achieving functionality, orother systems. Processing need not be limited to a geographic location,or have temporal limitations. For example, a processor can perform itsfunctions in “real-time,” “offline,” in a “batch mode,” etc. Portions ofprocessing can be performed at different times and at differentlocations, by different (or the same) processing systems.

Terms such as “component”, “module”, “circuitry”, “circuit”, “device”,“unit”, and “system” are intended to encompass hardware, software,firmware, or any combination thereof. For example, a system or componentmay be a process, a process executing on a processor, or a processor.Furthermore, a functionality, component or system may be localized on asingle device or distributed across several devices. The describedsubject matter may be implemented as an apparatus, a method, or articleof manufacture using standard programming or engineering techniques toproduce software, firmware, hardware, or any combination thereof tocontrol one or more computing devices.

As used herein, the terms “comprises,” “comprising,” “includes,”“including,” “has,” “having,” or any other variation thereof, areintended to cover a non-exclusive inclusion. For example, a process,product, article, or apparatus that comprises a list of elements is notnecessarily limited only those elements but may include other elementsnot expressly listed or inherent to such process, process, article, orapparatus. The term “exemplary” used throughout the specification means“serving as an example, instance, or exemplification” and does not mean“preferred” or “having advantages” over other embodiments.

Furthermore, the term “or” as used herein is generally intended to mean“and/or” unless otherwise indicated. For example, a condition A or B issatisfied by any one of the following: A is true (or present) and B isfalse (or not present), A is false (or not present) and B is true (orpresent), and both A and B are true (or present). As used herein,including the claims that follow, a term preceded by “a” or “an” (and“the” when antecedent basis is “a” or “an”) includes both singular andplural of such term, unless clearly indicated within the claim otherwise(i.e., that the reference “a” or “an” clearly indicates only thesingular or only the plural). Also, as used in the description hereinand throughout the claims that follow, the meaning of “in” includes “in”and “on” unless the context clearly dictates otherwise.

It will be appreciated that one or more of the elements depicted in thedrawings/figures can also be implemented in a more separated orintegrated manner, or even removed or rendered as inoperable in certaincases, as is useful in accordance with a particular application.Additionally, any signal arrows in the drawings/FIGS. should beconsidered only as exemplary, and not limiting, unless otherwisespecifically noted.

Thus, the scope of the invention is intended to be defined only in termsof the following claims as may be amended, with each claim beingexpressly incorporated into this description as an embodiment of theinvention.

Other variations to the disclosed embodiments can be understood andeffected by those skilled in the art in practicing the claimedinvention, from a study of the drawings, the disclosure, and theappended claims. In the claims, the word “comprising” does not excludeother elements or steps, and the indefinite article “a” or “an” does notexclude a plurality. A single processor, module or other unit mayfulfill the functions of several items recited in the claims.

The mere fact that certain measures are recited in mutually differentdependent claims does not indicate that a combination of these measuredcannot be used to advantage. A computer program may bestored/distributed on a suitable medium, such as an optical storagemedium or a solid-state medium supplied together with or as part ofother hardware, but may also be distributed in other forms, such as viathe Internet or other wired or wireless telecommunication systems. Anyreference signs in the claims should not be construed as limiting thescope.

What is claimed is:
 1. A method of determining a noise-robustacquisition configuration for operation of a sensor system, comprisingthe following steps in a noise scan: obtaining a sensor receive signalfrom the sensor system; determining a digital receive signal from thesensor receive signal by A/D conversion of the sensor receive signal ata predefined noise scan frequency; determining a plurality of decimateddigital receive signals by integer decimation of the digital receivesignal using two or more decimation rates that differ from each other,wherein each of the two or more decimation rates is associated with arespective candidate acquisition configuration; determining one or morenoise measures for multiple of the candidate acquisition configurationsusing one or more of the plurality of decimated digital receive signals;and using the one or more noise measures, determining the acquisitionconfiguration for operation of the sensor system from the candidateacquisition configurations.
 2. The method of claim 1, wherein the stepof determining the acquisition configuration comprises selecting apreferred noise measure from the one or more noise measures, wherein theacquisition configuration is set to correspond to the candidateacquisition configuration of the preferred noise measure.
 3. The methodof claim 2, wherein the preferred noise measure yields the lowest noiselevel of the one or more noise measures.
 4. The method of claim 1,wherein for each of the two or more decimation rates, correspondinggroups of decimated digital receive signals are determined, wherein ineach group, the decimated digital receive signals differ from each otherin a different starting phase.
 5. The method of claim 4, wherein one ormore of the noise measures are determined by an effective noise powerestimation, which comprises a determination of a sum ofphase-instantaneous noise measures over each of the decimated digitalreceive signals of one of the groups of decimated digital receivesignals.
 6. The method of claim 5, wherein the phase-instantaneous noisemeasure is a sum of samples of a decimated digital receive signalweighted with coefficients from a coefficient vector.
 7. The method ofclaim 1, wherein the acquisition configuration comprises at least one ormore of a sampling frequency for A/D conversion, an operating frequencyof a stimulus signal for operation of the sensor system, a scanduration, a number of samples to be acquired, and low-pass filtercoefficients.
 8. The method of claim 1, wherein the noise scan frequencyis significantly higher than an operating frequency of a stimulus signalduring operation of the sensor system.
 9. The method of claim 1, whereinthe two or more decimation rates are multiples of
 2. 10. The method ofclaim 1, wherein the sensor receive signal during the noise scan isacquired without a stimulus signal being applied to the sensor system.11. The method of claim 1, wherein the step of determining theacquisition configuration for operation of the sensor system from thecandidate acquisition configurations comprises comparing the one or morenoise measures with a noise threshold and in case the noise threshold isnot met by any of the noise measures: increasing a scan time of at leastone of the candidate acquisition configurations to obtain at least oneupdated candidate acquisition configuration; determining one or moreupdated noise measures for the at least one updated candidateacquisition configuration; and comparing the one or more updated noisemeasures with the noise threshold.
 12. The method of claim 11, whereinthe increased scan time is an integer multiple of a scan time of apreceding noise scan.
 13. The method of claim 1, comprising followingthe noise scan, operating the sensor system during an SN-scan using theacquisition configuration determined during the noise scan.
 14. Themethod of claim 13, comprising subsequently conducting multiple noisescans between two SN-scans, wherein the multiple noise scans usepredefined noise scan frequencies, wherein the predefined noise scanfrequencies of at least some of the multiple noise scans differ fromeach other.
 15. The method of claim 14, further comprising determiningan overall acquisition configuration for operation of the sensor systemduring an SN-scan from acquisition configurations obtained during thesubsequently conducted multiple noise scans.
 16. The method of claim 13,wherein an aperture time of an A/D conversion during the noise scan isidentical to or substantially an integer fraction of an aperture timeset for the SN-scan.
 17. The method of claim 1, wherein the sensorsystem is one or more of a capacitive sensor system and a touchscreensensor system.
 18. A non-transitory computer-readable medium includingcontents that are configured to cause a sensor circuit to conduct themethod of claim
 1. 19. A sensor circuit to determine an acquisitionconfiguration for operation of a sensor system, comprising: a sensorinterface for obtaining a sensor receive signal from the sensor system;an A/D converter to determine a digital receive signal from the sensorreceive signal by A/D conversion of the sensor receive signal at apredefined noise scan frequency; a decimation circuit, configured todetermine a plurality of decimated digital receive signals by integerdecimation of the digital receive signal using two or more decimationrates that differ from each other, wherein each of the two or moredecimation rates is associated with a respective candidate acquisitionconfiguration; a noise evaluation circuit, configured to determine oneor more noise measures for multiple of the candidate acquisitionconfigurations using one or more of the plurality of decimated digitalreceive signals; and a configuration circuit, configured to determinethe acquisition configuration for operation of the sensor system fromthe candidate acquisition configurations using the one or more noisemeasures.
 20. A capacitive touch sensing system, comprising: one or moreelectrodes, configured for capacitive sensing; and the sensor circuit ofclaim 19, which sensor circuit is connected to at least one of the oneor more electrodes.
 21. A method of determining a noise-robustacquisition configuration for operation of a communication system,comprising the following steps in a noise scan: obtaining a receivesignal from the communication system; determining a digital receivesignal from the receive signal by A/D conversion of the receive signalat a predefined noise scan frequency; determining a plurality ofdecimated digital receive signals by integer decimation of the digitalreceive signal using two or more decimation rates that differ from eachother, wherein each of the two or more decimation rates is associatedwith a respective candidate acquisition configuration; determining oneor more noise measures for multiple of the candidate acquisitionconfigurations using one or more of the plurality of decimated digitalreceive signals; and using the one or more noise measures, determiningthe acquisition configuration for operation of the communication systemfrom the candidate acquisition configurations.
 22. A communicationcircuit to determine an acquisition configuration for operation of acommunication system, comprising: a communication system interface forobtaining a receive signal from the communication system; an A/Dconverter to determine digital receive signal from the receive signal byA/D conversion of the receive signal at a predefined noise scanfrequency; a decimation circuit, configured to determine a plurality ofdecimated digital receive signals by integer decimation of the digitalreceive signal using two or more decimation rates that differ from eachother, wherein each of the two or more decimation rates is associatedwith a respective candidate acquisition configuration; a noiseevaluation circuit, configured to determine one or more noise measuresfor multiple of the candidate acquisitions configuration using one ormore of the plurality of decimated digital receive signals; and aconfiguration circuit, configured to determine the acquisitionconfiguration for operation of the communication system from thecandidate acquisition configurations using the one or more noisemeasures.
 23. A method of noise-robust acquisition operation of a sensorsystem, comprising: conducting at least one noise scan on the sensorsystem; and conducting at least one SN-scan on the sensor system;wherein an aperture time of an A/D conversion during the at least onenoise scan is identical to or substantially an integer fraction of anaperture time of an A/D conversion of the at least one SN-scan.